Plasmonically enhanced mid-IR light source based on tunable spectrally and directionally selective thermal emission from nanopatterned graphene


Abstract in English

We present a proof of concept for a spectrally selective thermal mid-IR source based on nanopatterned graphene (NPG) with a typical mobility of CVD-grown graphene (up to $3000$ cm$^2$V$^{-1}$s$^{-1}$), ensuring scalability to large areas. For that, we solve the electrostatic problem of a conducting hyperboloid with an elliptical wormhole in the presence of an in-plane electric field. The localized surface plasmons (LSPs) on the NPG sheet allow for the control and tuning of the thermal emission spectrum in the wavelength regime from 3 $mu$m to 12 $mu$m. The LSPs along with an optical cavity increase the emittance of graphene from about 2.3% for pristine graphene to 80% for NPG, thereby outperforming state-of-the-art pristine graphene light sources operating in the near-infrared (NIR) by a factor of 100. A maximum emission power per area of 11x10^3 W/m$^2$ at $T=2000$ K for a bias voltage of $V=23$ V is achieved by Joule heating. By generalizing Plancks theory and considering the nonlocal fluctuation-dissipation theorem with nonlocal response of surface plasmons in graphene in RPA, we show that the coherence length of the graphene plasmons and the thermally emitted photons can be as large as 13 $mu$m and 150 $mu$m, respectively, providing the opportunity to create phased arrays. The spatial phase variation of the coherence allows for beamsteering of the thermal emission in the range between $12^circ$ and $80^circ$ by tuning the Fermi energy. Our analysis of the nonlocal hydrodynamic response leads to the conjecture that the diffusion length and viscosity in graphene are frequency-dependent. Using finite-difference time domain (FDTD) calculations, coupled mode theory, and RPA, we develop the model of a mid-IR light source based on NPG, which will pave the way to graphene-based optical mid-IR communication, mid-IR color displays, mid-IR spectroscopy, and virus detection.

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